fiddler-labs/fiddler-examples
Jan 2025 – Jan 2025
1 Month active
Languages Used
JSONJupyter NotebookMarkdownPythoncsv
Technical Skills
Code CleanupData AnalysisData EngineeringData HandlingData ScienceDocumentation
Ash Cortez
PROFILE
Ash Cortez
Ash contributed to the fiddler-labs/fiddler-examples repository by developing the LLM Evaluation/Comparison Quickstart Guide and enhancing Jupyter Notebooks to streamline onboarding and model evaluation workflows. Leveraging Python and Pandas, Ash unified model naming conventions, improved dataset path handling, and refined the get_or_create logic to ensure consistent project setup. The work included notebook execution state improvements and the addition of visual metric cards to support clearer analysis. Ash also addressed reliability by fixing minor bugs and maintaining documentation, including updating tutorial screenshots and section titles. This focused, high-quality engineering improved both the usability and maintainability of the LLM evaluation tools.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
14Total
Bugs
1
Commits
14
Features
1
Lines of code
12,375
Activity Months1
Your Network
16 people
Work History
January 2025
14 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for fiddler-labs/fiddler-examples: Delivered the Fiddler LLM Evaluation/Comparison Quickstart Guide and Notebook Enhancements, consolidating onboarding flow, model naming consistency, dataset path handling, get_or_create usage, and notebook execution state improvements, complemented by visual assets for metric cards. Also performed targeted quality work to maintain reliability (notebook maintenance, minor fixes) and refined documentation/assets.
14 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for fiddler-labs/fiddler-examples: Delivered the Fiddler LLM Evaluation/Comparison Quickstart Guide and Notebook Enhancements, consolidating onboarding flow, model naming consistency, dataset path handling, get_or_create usage, and notebook execution state improvements, complemented by visual assets for metric cards. Also performed targeted quality work to maintain reliability (notebook maintenance, minor fixes) and refined documentation/assets.
January 2025
Activity
Loading activity data...
Quality Metrics
Correctness93.0%
Maintainability93.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPythoncsv
Technical Skills
Code CleanupData AnalysisData EngineeringData HandlingData ScienceDocumentationFiddlerJupyter NotebookJupyter NotebooksLLMLLM EvaluationLLM ObservabilityMachine LearningObservabilityPandas
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline